Triple
T11170638
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rorschach–Heiden rack railway |
E264263
|
entity |
| Predicate | rackSectionLength |
P61783
|
FINISHED |
| Object | majority of line |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: majority of line | Statement: [Rorschach–Heiden rack railway, rackSectionLength, majority of line]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: rackSectionLength Context triple: [Rorschach–Heiden rack railway, rackSectionLength, majority of line]
-
A.
borderSectionLength
Indicates the measured length of a specific segment of a shared border between two geographic or administrative areas.
-
B.
hasSectionLength
chosen
Indicates that an entity is associated with a specific length value for one of its sections.
-
C.
coneLength
Indicates the length measurement of a cone-shaped structure associated with an entity.
-
D.
standardSectionArea
Indicates that one entity specifies the standard or nominal cross-sectional area associated with another entity.
-
E.
buildingSection
Indicates a relationship where one entity is a specific section, part, or subdivision of a larger building.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d6aa9dafac8190bd90d2c74f661aa7 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e8952e248190b0751669e8c960b7 |
completed | April 9, 2026, 5:57 p.m. |
| PD | Predicate disambiguation | batch_69d75cf0e6e88190973694abe2990973 |
completed | April 9, 2026, 8:01 a.m. |
Created at: April 8, 2026, 9:29 p.m.